Staff AI Engineer - AI Infrastructure & Agentic Platform
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff AI Engineer - AI Infrastructure & Agentic Platform based in the United States.
This role offers the opportunity to shape the foundation of an AI-native technology ecosystem within a fast-growing healthcare marketplace.
You will own the architecture and evolution of AI infrastructure powering intelligent workflows, retrieval systems, and agent-based applications.
Working at the intersection of software engineering, machine learning, and cloud infrastructure, you will build scalable solutions that create measurable business impact.
You will take ownership of advanced AI capabilities, including retrieval augmentation, agent orchestration, knowledge platforms, and AI governance.
This position provides significant autonomy, technical influence, and the chance to define how enterprise AI systems are designed and operated.
You will collaborate with engineering leaders and cross-functional teams to deliver secure, reliable AI solutions in a regulated healthcare environment.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff AI Engineer - AI Infrastructure & Agentic Platform based in the United States.
This role offers the opportunity to shape the foundation of an AI-native technology ecosystem within a fast-growing healthcare marketplace.
You will own the architecture and evolution of AI infrastructure powering intelligent workflows, retrieval systems, and agent-based applications.
Working at the intersection of software engineering, machine learning, and cloud infrastructure, you will build scalable solutions that create measurable business impact.
You will take ownership of advanced AI capabilities, including retrieval augmentation, agent orchestration, knowledge platforms, and AI governance.
This position provides significant autonomy, technical influence, and the chance to define how enterprise AI systems are designed and operated.
You will collaborate with engineering leaders and cross-functional teams to deliver secure, reliable AI solutions in a regulated healthcare environment.
Accountabilities:
- Evolve the AI knowledge platform by improving retrieval, indexing, and synthesis capabilities to support internal engineering tools and customer-facing applications.
- Architect and operate agentic infrastructure in cloud environments, enabling multi-step AI systems that can plan, retrieve information, and execute actions with strong reliability and cost controls.
- Design advanced retrieval architectures, including graph-based and relationship-aware approaches, to improve knowledge discovery and enable more intelligent AI agents.
- Build and maintain platform APIs that allow product engineering teams to easily leverage AI infrastructure capabilities.
- Develop reference implementations for AI agents supporting use cases such as operational support, customer assistance, and automated workflows.
- Establish AI infrastructure cost management practices by monitoring model usage, compute resources, storage expenses, and implementing governance mechanisms.
- Improve AI system observability through metrics, structured logging, evaluation frameworks, and performance monitoring.
- Partner with engineering teams and leadership to define AI platform strategy, technical standards, and long-term architecture.
- Ensure AI systems meet security, privacy, and compliance expectations within a regulated healthcare technology environment.
- 7+ years of professional software engineering experience, including at least 2 years building and operating production AI or LLM-powered systems.
- Strong expertise in retrieval engineering, including hybrid search, re-ranking, query transformation, context management, and production retrieval evaluation.
- Experience building and operating agentic AI systems involving tool usage, multi-step reasoning, orchestration, and model routing decisions.
- Strong software engineering skills with experience in Go, Python, TypeScript, or similar modern programming languages.
- Experience deploying and managing AI workloads on cloud AI platforms such as AWS Bedrock or Azure AI Foundry, including identity management, security controls, and model governance.
- Hands-on Terraform experience with the ability to design and provision infrastructure independently.
- Familiarity with AI observability practices, including monitoring model performance, latency, cost, and quality regressions.
- Experience designing scalable cloud-native systems and production infrastructure.
- Understanding of privacy, security, and compliance requirements for sensitive data environments such as HIPAA-regulated platforms.
- Strong problem-solving skills with the ability to operate independently, define technical direction, and influence engineering teams.
- Healthcare technology experience is a plus but not required.
- High-growth environment with opportunities for career development and technical ownership.
- Flexible remote work options.
- Additional vacation days to support work-life balance.
- Modern office environment with recreational facilities and nearby amenities.
- Comprehensive private medical coverage.
- Sports and wellness benefits.
- Life and accident insurance coverage.
- Opportunity to work on impactful AI solutions transforming healthcare workforce technology.
As a Staff AI Engineer, you will lead the design, development, and operation of the AI infrastructure layer, creating scalable platforms that enable intelligent applications across the organization. You will combine deep AI engineering expertise with strong software development practices to build reliable, production-grade AI systems.
Requirements:
The ideal candidate is a highly experienced AI infrastructure engineer with a strong background in production AI systems, retrieval technologies, cloud platforms, and scalable software engineering. You should be comfortable owning complex technical initiatives and driving architecture decisions across teams.